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Barclays is also working on several AI projects, looking to leverage AI technology in its trading, lending, and risk management divisions. One example is the new innovative talking cash machines/ATMs which has been designed to help one-fifth of UK residents who are disabled.

Experian DataLabs were challenged to find a solution whereby banks and other financial service providers could maximise Open Banking data and transactional data sharing to better inform decisions. Machine learning offers a much more granular approach for the cases which require more accuracy than classical models.

The Computational and Intelligent Systems Engineering Laboratory aims at promoting the modern Data Science among young students at University of Sannio, by investigating and experimenting the application of advanced techniques of artificial intelligence, data analysis and decision making to problems of industrial and practical interest.

"Classification-based Financial Markets Prediction using Deep Neural Networks". In this paper Diego Klabjan helps describe how DNNs are used to predict movements in the financial market by explaining the configuration and training approach and demonstrating the application strategy.

Zhengyao Jiang writer from the University of Liverpool, wrote a paper on usage of algorithms of «Reinforcement Learning» in cryptocurrency markets. The results are impressive: using historical data for 8 months, the program achieved a 10-fold increase in the size of the portfolio at 30-minute intervals. To achieve this profit it took a little less than two months.

“In the context of accelerated digital transformation, the human factor is more important than ever. By creating a position of Chief Scientist, Artificial intelligence, and by hiring Manuel, we want to clearly orient our AI initiatives and accelerate innovation,” explained David Furlong, Senior Vice-President, Artificial intelligence, Venture Capital and Blockchain at National Bank.

Why Attend

Extraordinary Speakers

Discover advances in deep learning tools and techniques from the world's leading innovators across industry, academia and the financial sector. Speakers will share insights into recent breakthroughs in technical advancements and fintech applications including financial forecasting & compliance.

Discover Emerging Trends

Learn about deep learning applications in the financial sector from algorithms to forecast financial data, to tools used for data mining & pattern recognition in financial time series, to scaling predictive models, to stock market prediction, to using blockchain technology.

Expand Your Network

A unique opportunity to interact with industry leaders, influential technologists, data scientists & founders leading the deep learning revolution. Learn from & connect with 200+ industry innovators sharing best practices to improve regulations, security and risk in the financial sector.

Who Should Attend

Data Scientists

Financial Regulators

CTOs

Directors of Innovation

Data Engineers

Venture Capitalists

Heads of Data Science

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30 speakers

200 leading technologists & innovators

Group brainstorming sessions

Interactive workshops

12 + hours of networking

Access to all the filmed presentations

Discover technology shaping the future

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View the summit brochure and all the information you need to convince your boss that attending the summit will help future-proof your business.

“The value of the event is to find out where AI currently stands in the financial service industry as well as the opportunities to discover new AI application ideas, to network with professors and industry practitioners”

Data Scientist, The World Bank

“Common machine learning methods are often ineffective in certain real-world settings where data is scarce or very messy. It was great to discuss what works and what doesn’t with a mix of industry practitioners and applied researchers”